CN112508608B - Popularization activity configuration method, system, computer equipment and storage medium - Google Patents
Popularization activity configuration method, system, computer equipment and storage medium Download PDFInfo
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Abstract
A method, system, computer device and storage medium for configuring a promotional activity are provided, the method comprising: selecting a customer group to be promoted; acquiring a first parameter and a second parameter of a client group in each historical promotion activity related to the activity to be promoted, wherein the first parameter represents a difference value of resource variation of a promotion group and a comparison group of the client group in one historical promotion activity; the second parameter represents the proportion of resource change configuration quantity of the client group in the ordering position from small to large of the client resource change quantity in the comparison group in a historical popularization activity; and determining the resource change allocation amount of the activities to be promoted according to the first parameter and the second parameter of the client group in each historical promotion activity related to the activities to be promoted. The feedback of the client group in the historical popularization activities is fused into the configuration of the resource change configuration quantity of the popularization activities, the resource change configuration quantity of the popularization activities can be accurately configured, and the popularization activities with high client participation degree, high responsiveness and high standard reaching rate are designed.
Description
Technical Field
The present disclosure relates to a method, a system, a computer device and a storage medium for popularizing activity configuration.
Background
The configuration of resource variation of online popularization activities in the existing bank field is mostly configured according to business indexes determined by some empirical rules.
The following defects exist in the way of manually configuring the resource variation through the service index: the resource variation setting precision is low, and irrationality exists. Resource variation sets up too high, and most customers can not reach, and the too low customer of resource variation can both reach, and that is to say, resource variation sets up unreasonable will be unfavorable for the variable quantity that accurate assurance customer probably resource promoted, and then can't design the popularization activity that is fit for the customer and participates in.
Disclosure of Invention
This paper is arranged in solving prior art, and there is the defect that the accuracy is low in the artifical mode that sets up the resource change configuration volume of promoting the activity through experience, and then makes the variable quantity that promotes activity designer can't accurate hold customer resource promotion, and then can't design out the popularization activity that is fit for customer participation.
In order to solve the above technical problem, a first aspect of the present disclosure provides a method for configuring a promotional campaign, including:
selecting a client group to be promoted, wherein the client group comprises a promotion group and a comparison group;
acquiring a first parameter and a second parameter of the client group in each historical promotion activity related to the activity to be promoted, wherein the first parameter represents a difference value of resource variation of a promotion group and a comparison group of the client group in one historical promotion activity; the second parameter represents the proportion of resource change configuration quantity of the client group in the ordering position from small to large of the client resource change quantity in the comparison group in a historical popularization activity;
and determining the resource change allocation amount of the activities to be promoted according to the first parameter and the second parameter of the client group in each historical promotion activity related to the activities to be promoted.
In a further embodiment of the present disclosure, the promotion group and the control group in the customer group have the same number of customers, and the characteristic distributions of the customers are consistent and come from the same predetermined area.
In a further embodiment of this document, the calculating of the first parameter of the customer base in each historical promotion activity includes:
for each historical promotional activity Xi, the following operations are performed:
calculating the variation of the popularization group resources and the variation of the comparison group resources of the client group in the historical popularization activity Xi;
and subtracting the variation of the popularization group resource of the client group in the historical popularization activity Xi from the variation of the reference group resource, and calculating to obtain a first parameter of the client group in the historical popularization activity Xi.
In a further embodiment of this document, calculating the variation of the promotion group resource and the variation of the reference group resource of the client group in the historical promotion activity includes:
respectively calculating the total number of customers of the promotion group and the comparison group in the customer group;
respectively calculating the variation of the total resource of the promotion group and the variation of the total resource of the comparison group in the historical promotion activities of the client group;
calculating the promotion group per-capita resource variation of the client group in the historical promotion activity by dividing the promotion group total resource variation of the client group in the historical promotion activity by the promotion group total client number;
and dividing the comparison group total resource variation of the client group in the historical popularization activity by the comparison group client total number to calculate the comparison group per-capita resource variation of the client group in the historical popularization activity.
In a further embodiment of this document, determining a resource change allocation amount of the to-be-promoted activity according to a first parameter and a second parameter of the client group in each historical promotion activity related to the to-be-promoted activity includes:
screening out the historical popularization activities with the first parameter of N before the ranking according to the first parameter of the client group in each historical popularization activity related to the activity to be popularized;
and calculating the resource change allocation amount of the activities to be promoted according to the screened second parameters of the historical promotion activities of the N-th top ranking.
In a further embodiment of this document, calculating, according to the screened second parameter of the historical promotional activity of the top-ranked N, a resource change allocation amount of the activity to be promoted, includes:
carrying out maximum value solving or average processing on the screened second parameter of the historical popularization activity of the N before ranking;
taking the calculated value as a second parameter configuration quantity of the activity to be promoted;
and calculating the resource change allocation quantity of the activity to be promoted according to the second parameter allocation quantity and the latest M historical promotion activities related to the activity to be promoted.
In a further embodiment of this document, calculating a resource change configuration amount of the activity to be promoted according to the second parameter configuration amount and the recent M historical promotion activities related to the activity to be promoted includes:
screening out resource variation of the clients in the comparison group of the activities to be promoted from each historical promoting activity Xj in the latest M historical promoting activities, and sequencing the resource variation of the screened clients from small to large;
and taking the average value or the maximum value of the resource variation quantity of which the sequencing position accounts for a second parameter configuration quantity in the latest M historical popularization activities as the resource variation configuration quantity of the activities to be popularized.
A second aspect herein provides a promotional campaign configuration method, comprising:
the client group selection module is used for selecting a client group to be promoted, and the client group comprises a promotion group and a comparison group;
the parameter determining module is used for acquiring a first parameter and a second parameter of the client group in each historical promotion activity related to the activity to be promoted, wherein the first parameter represents a difference value of resource variation of a promotion group and a comparison group of the client group in one historical promotion activity; the second parameter represents the proportion of the resource change configuration quantity of the client group in the ranking position of the client resource change quantity from small to large in the comparison group in the historical popularization activity;
and the configuration module is used for determining the resource change configuration amount of the activities to be promoted according to the first parameter and the second parameter of the client group in each historical promotion activity related to the activities to be promoted.
A third aspect of the present document provides a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the promotional activity configuration method of any of the preceding embodiments when executing the computer program.
A fourth aspect herein provides a computer readable storage medium storing an executable computer program which, when executed by a processor, implements a promotional activity configuration method as described in any of the preceding embodiments.
According to the popularization activity configuration method, the popularization activity configuration system, the computer equipment and the storage medium, a client group to be popularized is selected, and the client group comprises a popularization group and a comparison group; acquiring a first parameter and a second parameter of the client group in each historical promotion activity related to the activity to be promoted, wherein the first parameter represents a difference value of resource variation of a promotion group and a comparison group of the client group in a historical promotion activity; the second parameter represents the proportion of the resource change configuration quantity of the customer group in the ranking position of the customer resource change quantity from small to large in the comparison group in the historical popularization activity; according to the first parameter and the second parameter of the client group in each historical popularization activity Xi related to the activity to be popularized, the resource change allocation quantity of the activity to be popularized is determined, the feedback of the client group in the historical popularization activity (namely the relation between the first parameter and the second parameter of the client group in the historical popularization activity) can be fused into the allocation of the resource variation quantity of the popularization activity under the condition that a multidimensional client group figure is lacked, the resource change allocation quantity of the popularization activity can be accurately allocated, and therefore the popularization activity with high client participation degree, high responsiveness and high standard reaching rate is designed.
In order to make the aforementioned and other objects, features and advantages of the present invention comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the embodiments or technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 shows a flow diagram of a method of promotional activity configuration according to an embodiment herein;
FIG. 2 is a flow chart illustrating a first parameter calculation process according to embodiments herein;
FIG. 3 is a flow chart illustrating a second parameter calculation process according to embodiments herein;
FIG. 4 shows a flow diagram of a resource change configuration amount determination process according to an embodiment herein;
FIG. 5 illustrates a first architectural diagram of a generalized activity configuration system of an embodiment herein;
fig. 6 shows a second block diagram of a promotional activity configuration system according to an embodiment herein;
FIG. 7 illustrates a flow diagram of a method for promotional activity configuration according to an embodiment herein;
FIG. 8 is a block diagram of a computer device according to an embodiment of the present disclosure.
Description of the figures the symbols:
510. a customer group selection module;
520. a parameter determination module;
530. a configuration module;
540. a parameter calculation module;
541. a first parameter calculation unit;
542. a second parameter calculation unit;
802. a computer device;
804. a processor;
806. a memory;
808. a drive mechanism;
810. an input/output module;
812. an input device;
814. an output device;
816. a presentation device;
818. a graphical user interface;
820. a network interface;
822. a communication link;
824. a communication bus.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments herein without making any creative effort, shall fall within the scope of protection.
In an embodiment of the present disclosure, as shown in fig. 1, fig. 1 is a flowchart illustrating a method for configuring a promotional activity according to an embodiment of the present disclosure, and this embodiment is used to solve a defect in the prior art that a method for manually setting a resource change configuration amount of a promotional activity through experience has low accuracy. The embodiment can be operated in an intelligent terminal and a server, including a smart phone, a tablet computer, a desktop computer, and the like, and the specific implementation manner is not limited herein. The configuration requirements of the intelligent terminal and the server are not high, and the configuration of the conventional dual-core 8GB RAM can be realized.
Specifically, the configuration method for the promotion activities comprises the following steps:
In the embodiment, a client group of activities to be promoted is selected, and a first parameter and a second parameter of the client group in each historical promotion activity related to the activities to be promoted are obtained, wherein the first parameter represents a difference value of resource variation of a promotion group and a comparison group of the client group in one historical promotion activity; the second parameter represents the proportion of resource change configuration quantity of the client group in the ordering position from small to large of the client resource change quantity in the comparison group in a historical popularization activity; the resource change allocation amount of the to-be-promoted activities is determined according to the first parameters and the second parameters of the client group in each historical promotion activity related to the to-be-promoted activities, the feedback of the client group in the historical promotion activities (namely the relation between the first parameters and the second parameters of the client group in the historical promotion activities) can be fused into the allocation of the resource variation amount of the promotion activities under the condition that a multidimensional client group figure is lacked, the resource change allocation amount of the promotion activities can be accurately allocated, and the promotion activities with high client participation degree, high responsiveness and high standard reaching rate are designed. Through constantly optimizing first parameter and second parameter, can improve the popularization effect, according to promoting the popularization group in the effect screening customer crowd, and then promote the group quality in the promotion group.
In detail, in the step 110, the selection of the customer group may be selected according to a promotion policy of the promotion activity or a manual manner, and the specific selection manner is not limited herein. The promotion activities include promoted products, and specific reasons of the products are related to the application field of the promotion activity configuration method, for example, the products are applied to the bank field, the products of the promotion activities include but are not limited to insurance services, financial products and the like, and also, for example, the products of the promotion activities include but are not limited to broadband services, telephone charge services and the like. The method can also be applied to other fields except banks, and the like, and the popularization activity configuration method can be used in the field with popularization requirements.
In order to implement different activity popularization in different regions, that is, different popularization activities are launched in different regions, and different resource change configuration amounts are set for the popularization activities, the client group may be divided according to geographic positions, where the division of the geographic positions includes, but is not limited to, division of an existing administrative region, division according to a region to which a division organization belongs, division according to a development degree grade (for example, division into a region in a first-line city such as shanghai, etc.), division according to user activity characteristics (for example, user activity modes in guangzhou Shenzhen region are similar, and may be divided into the same region), and a specific division mode of the client group is not limited herein. Taking a bank promotion activity as an example, the customer groups can be configured according to branches and generation wage files, that is, each generation wage file corresponding to each branch corresponds to one customer group, customers in the customer groups can be averagely divided into promotion groups and comparison groups, and part of the customers can be extracted from all the customers to form the promotion groups and the comparison groups. Further, the client group or the integrated area may be set according to characteristics of the client (for example, payroll level, asset level, etc. of the client), and the client group may be set according to characteristics of the client.
The customers in the promotional group can receive promotions for actually producing a promotional effect. And the clients in the contrast group do not receive the promotion of the promotion activities, and are used for comparing the promotion effects of the promotion activities. In order to ensure the accuracy of the comparison effect of the comparison group, the promotion group in each customer group has the same number of customers as the comparison group, the characteristics of the customers are distributed uniformly and come from the same predetermined area, wherein the characteristics of the customers comprise attribute quantity and statistic quantity, wherein the attribute quantity comprises but is not limited to age, attribute, income, work type and the like, the statistic quantity comprises but is not limited to historical expense amount, historical transfer, loan amount and the like, and the specific content and number of the characteristics of the customers are not limited herein. In some embodiments, the customers in the promotion group and the comparison group in the customer group can be adjusted adaptively, and in other embodiments, the customers in the comparison group in the customer group are not changed and are long-term comparison groups, for example, no active promotion is performed for one year or several years.
In the above step 120, the historical popularization activities related to the activities to be promoted refer to the same type of popularization activities, and the same type of popularization activities may be determined according to the products and the amounts related to the popularization activities, for example, the popularization activities of the financial products may be classified into one type, the popularization activities of the fund products may be classified into one type, and the like.
The resource variation may be calculated from resource amounts of time before and after the promotion activity is performed, and includes, but is not limited to, per-capita asset variation, per-capita conversion rate (an average of customer conversion rates, where customer conversion refers to purchasing a product associated with the promotion activity or responding to a promotion activity requirement), and the like, and any amount that can be changed due to promotion of the promotion activity may be used as the resource variation described herein, which is not specifically limited herein. Assets include, but are not limited to, liquidity assets, including deposits, accounts receivable and prepaid, inventory, etc., long term investments, including bonds, etc., fixed assets, including houses, buildings, machinery, vehicles, etc., intangible assets, including articles, periodicals, patents, etc.
The first parameter can reflect the variation of the per-person net resource of the client caused by the promotion activity, and the second parameter can reflect the requirement of the resource variation allocation amount by what percentage of clients can reach in a natural state (namely, in a state that the client does not acquire the promotion activity). The specific calculation process of the first parameter and the second parameter is described in the following embodiments, and will not be described in detail here.
In specific implementation, the first parameter and the second parameter of the customer base in each historical promotion activity related to the activity to be promoted can be obtained from a database related to the customer base, the information of the historical promotion activity and the corresponding first parameter and second parameter are stored in the database, and specifically, the database can be stored according to a field shown in a table I.
Table one:
| historical promotional Activity numbering | Brief introduction to promotional Activities | First parameter | Second parameter |
And after each promotion activity is finished, immediately calculating a first parameter and a second parameter of the promotion activity, and storing the first parameter and the second parameter in a database related to the customer group.
In specific implementation, historical popularization activities of the client group related to the activities to be performed in step 110 may also be obtained first, and then the first parameter and the second parameter of the client group in each historical popularization activity are calculated according to the resource variation of the client group in each historical popularization activity.
In the step 130, the resource change allocation amount of the activity to be promoted is determined according to the first parameter and the second parameter of the client group in each historical promotion activity related to the activity to be promoted, based on the principle of increasing the resource change amount of the client as much as possible. The resource change configuration quantity can properly increase the resource increase quantity of some clients, and further increase the client viscosity. The promotion activity designer can design details of promotion activities, such as specific amount of preferential strength and the like, according to the resource change configuration amount, and the specific determination process refers to the following embodiments.
In an embodiment of this document, the customer conversion rate may be calculated by using a fusion classification model corresponding to the activity to be promoted, specifically, the method includes:
(1) And calculating to obtain the value probability of the conversion variable of each client in the client group according to the characteristics of each client in the client group and the fusion classification model corresponding to the activity to be promoted.
Each type of promotion activity corresponds to a fusion classification model, and the corresponding relationship is shown in a table two:
watch 2
| Type of promotional activity | Fusion classification model |
| Type 1 | Fusion classification model 1 |
| Type 2 | Fusion classification model 2 |
| Type 3 | Fusion classification model 3 |
| … | … |
Each promotional activity type includes a plurality of promotional activities, and promotional activities relating to the same type of product can be set to the same promotional activity type.
In an embodiment of this document, each fusion classification model may be obtained by training a conversion result of a client group in a similar historical popularization activity M, and specifically, the building process of the fusion classification model includes:
firstly, converting the conversion result of the clients in the client group in the same-type historical popularization activity M by using the following rules:
wherein Z represents a conversion variable, T represents a promotion group, C represents a control group, Y represents a conversion result, G = T represents that a client is from the promotion group, G = C represents that the client is from the control group, Y =1 represents that the conversion result is conversion, Y =0 represents that the conversion result is non-conversion, Z =1 represents a first value, and Z =0 represents a second value;
secondly, the characteristics of the customers in the popularization group and the comparison group are used as input, the value-taking probability of the conversion variable of the customers is used as output, and a fusion classification model is obtained by adopting a deep learning method for training.
In the embodiment, the fusion classification model established by introducing the conversion variable can directly calculate the promotion conversion rate, and can fuse the group data of the contrast group and the promotion group, thereby avoiding error amplification caused by the double classification model.
In some specific embodiments, the training by using the deep learning method to obtain the fusion classification model includes the following steps: establishing an N-layer neural network model, wherein the first N-1 layer adopts a ReLU function, and the last layer adopts a Sigmod activation function; initializing the neural network model; taking the characteristics of the clients in the comparison group and the promotion group as input, and taking the value probability of the conversion variable of the clients as output; constructing a loss function according to the input, the output and the neural network model; optimizing the neural network model according to a loss function; and the optimized neural network model is the fusion classification model.
In a specific embodiment, the optimized neural network model finally selects 4 layers of neural networks, and the first 3 layers adopt a RuLU function (Rectified Linear Unit). In other embodiments, the number of layers of the neural network model may be set according to requirements, which is not limited herein. In the embodiment, the calculation of the modeling process can be simplified by setting the front N-3 layers as the RuLU function, the calculation speed of modeling is improved, the disappearance of the gradient is prevented, the network has sparsity, and overfitting is reduced. The solution can be facilitated by setting the last layer to a Sigmod activation function, ensuring data amplitude.
In one embodiment, a Kaiming uniform distribution is used to initialize the neural network model.
In a specific embodiment, the transition variable value probabilities include P (Z = 1|X) and/or P (Z = 0|X), where P (Z = 1|X) represents the probability that the customer transformation result in the promotion group is a transformation and the customer transformation result in the control group is an untransformation, and P (Z = 0|X) represents the probability that the customer transformation result in the promotion group is an untransformation and/or the customer transformation result in the control group is a transformation. The characteristics of the customers can be determined according to the characteristics of the promotion activities, the characteristics of the customers of the same type of promotion activities can be the same, and the characteristics are not limited in the text.
In one embodiment, the selected loss function is, for example, a two-class cross entropy loss function. This embodiment is through setting up the loss function into two categorised cross entropy loss functions, can be convenient for derive, improves data and seeks speed. In particular, other types of loss functions may be used, and are not limited herein.
In some embodiments, an Adam (Adaptive moment estimation) optimizer can be selected to optimize the neural network model, the optimization method can accelerate the fitting of high-dimensional data, the attenuation of step length does not need to be set, and the obtained parameter value is relatively stable. In other embodiments, algorithms such as SGD may be selected according to a random gradient descent method, which is not specifically limited herein.
(2) And calculating the customer conversion rate of each customer by using the following formula according to the conversion variable value probability of each customer.
Δ (X) =2 × P (Z = 1|X) -1; or
Δ(X)＝1-2×P(Z＝0|X)；
Wherein Δ (X) represents the customer conversion rate, X represents the customer characteristics, Z =1 represents the first value, P (Z = 1|X) represents the probability that the customer conversion variable to be analyzed is the first value, and P (Z = 0|X) represents the probability that the customer conversion variable to be analyzed is the second value.
In an embodiment, as shown in fig. 2, the calculation process of the first parameter described herein includes, for each historical promotional activity Xi, the following operations:
watch III
| Historical promotional Activity numbering | Promotion group | Control group |
| 1 | Resource variance 11 | Resource variance 12 |
| 2 | Resource variation 21 | Resource variation 21 |
| … | … | … |
In detail, the promoted group resource variation and the control group resource variation may be total resource variation of clients in each group, or may also be per-capita resource variation, which is not limited herein, and the following describes a specific execution process of the step 210 by taking the per-capita resource variation as an example, and includes:
step 211, respectively calculating the total number of customers of the promotion group and the comparison group in the customer group, wherein the total number of customers of the promotion group is the same as that of customers of the comparison group under normal conditions;
step 212, calculating the variation of the total resource of the promotion group and the variation of the total resource of the comparison group in the historical promotion activity Xi by the customer group according to the following formulas:
wherein S is xi Representing the total resource variation of the promotion group or the control group in the historical promotion activity Xi, N representing the total number of customers of the promotion group or the control group, y j Representing the resource variation of the jth client in the promotion group or the comparison group;
step 213, dividing the total resource variation of the promotion group in the historical promotion activity Xi by the total number of the promotion group clients by the client group, and calculating to obtain the per-capita resource variation of the promotion group in the historical promotion activity Xi by the client group;
step 214, dividing the comparison group total resource variation of the client group in the historical popularization activity Xi by the comparison group client total number, and calculating to obtain the comparison group per-person resource variation of the client group in the historical popularization activity Xi.
In one embodiment herein, as shown in fig. 3, the calculation process of the second parameter includes, for each historical promotional activity Xi, performing the following operations:
and step 330, calculating a second parameter of the client group in the historical promotion activity according to the ranking ratio.
For example, if the number of clients in a client group is 100, the resource change amount is the client conversion rate, the ranking result is 0.24, 0.27, 0.28, 0.30, 0.31, 0.32, 0.4 …, and the resource change allocation amount of the historical promotional activity is, for example, 0.40, the ranking of the resource change allocation amount in this example can be determined to be 7, so that the ranking ratio can be determined to be 7/100% =7%, that is, the second parameter can be determined to be 7%.
In specific implementation, the proportion of the positions in the comparison group in the order from large to small according to the resource change configuration amount can be used for calculating a second parameter, and a specific calculation formula is as follows: 1-P, wherein P represents the proportion of the resource change configuration quantity in the ranking positions of the client resource change quantity in the comparison group from large to small.
In an embodiment of this document, as shown in fig. 4, the step 130 determines, according to a first parameter and a second parameter of the client group a in each historical promotional activity related to the to-be-promoted activity, a resource change allocation amount of the to-be-promoted activity, including:
and step 420, calculating the resource change allocation amount of the activities to be promoted according to the screened second parameters of the historical promotion activities of the N-th top ranking.
In detail, N is a positive integer greater than or equal to 1, and specific values thereof may be set according to requirements, which is not limited herein. When N =1, the historical promotional activity with the largest first parameter is screened out in step 410.
In some embodiments, the step 420 of calculating the resource change configuration amount of the activity to be promoted according to the screened second parameter of the historical promotion activity of the top-ranked N includes: and carrying out average processing on the resource change configuration quantity corresponding to the second parameter of the historical popularization activity of the N before ranking, and taking the average value as the resource change configuration quantity of the activity to be popularized. For example, if N is 3, and the resource change configuration amounts of the historical popularization activities in the top 3 are 0.85, 0.65, and 0.6, respectively, then the average value of 0.7 is taken as the resource change configuration amount of the activity to be popularized.
In other embodiments, in order to ensure the effectiveness of the resource change allocation amount, the step 420 calculates the resource change allocation amount of the activity to be promoted according to the screened second parameter of the historical promotion activity of the top-ranked N, including:
step 421, carrying out maximum value calculation or average calculation on the screened second parameter of the historical popularization activity of the N before ranking;
step 422, using the calculated value as a second parameter configuration quantity of the activity to be promoted;
and 423, calculating the resource change allocation quantity of the activity to be promoted according to the second parameter allocation quantity and the latest M historical promotion activities related to the activity to be promoted.
In detail, step 423 calculates a resource change configuration amount of the activity to be promoted according to the second parameter configuration amount and the recent M historical promotion activities related to the activity to be promoted, including:
(1) For each historical promoting activity Xj in the latest M historical promoting activities, the following operations are executed: and screening out the resource variation of the clients in the comparison group of the activities to be promoted from the historical promotion activities Xj, and sequencing the resource variation of the clients in the screened comparison group of the activities to be promoted from small to large. Specifically, the value of M may be set according to actual requirements, which is not limited herein.
(2) And taking the average value or the maximum value of the resource variation quantity taking the sequencing position in the latest M historical popularization activities as a second parameter configuration quantity as the resource variation configuration quantity of the activities to be popularized.
For example, if the calculated second parameter configuration amount is 0.8, m is 1, the latest 1 historical promotional activity related to the activity to be promoted is recorded as Xk, the comparison group of the activity to be promoted is 100 persons, and only 90 persons of the 100 persons are included in the historical promotional activity Xk. Step 423 implements the process of: sequencing the resource variation of the 90 people in the historical popularization activity Xk from small to large; and taking the resource variation with the position ratio of 0.8 in the sequence as the resource variation configuration quantity of the activity to be promoted.
For another example, if the calculated second parameter configuration amount is 0.8, the value of m is 2, it is noted that the latest 1 historical promotional activities related to the to-be-promoted activity are Xk1 and Xk2, the comparison group of the to-be-promoted activities is 100 persons, and only 90 persons of the 100 persons are included in the promotional activities Xk1 and Xk2. Step 423 implements the process of: respectively sequencing the resource variation of the 90 people in the historical popularization activities Xk1 and Xk2 from small to large to obtain two sequencing results; and taking the average value of the resource variation with the position ratio of 0.8 in the two sequencing results as the resource variation configuration quantity of the activity to be promoted. For example, if the resource variation amount with the position ratio of 0.8 in one ranking result is 2000, and the resource variation amount with the position ratio of 0.8 in another ranking result is 1900, 1950 is taken as the resource variation allocation amount of the activity to be promoted.
Based on the same inventive concept, a promotional activity configuration system is also provided herein, as described in the embodiments below. Because the principle of solving the problem of the popularization activity configuration system is similar to that of the popularization activity configuration method, the popularization activity configuration system can be implemented by referring to the popularization activity configuration method, and repeated parts are not described again. The promotion activity configuration system comprises a plurality of functional modules, which can be realized by special or general chips, and can also be realized by software programs, and the promotion activity configuration system is not limited in the text.
Specifically, as shown in fig. 5, the configuration system for promotion activities includes:
a client group selection module 510, configured to select a client group to be promoted, where the client group includes a promotion group and a comparison group, and the promotion group and the comparison group in the client group have the same number of clients and have the same characteristic distribution of the clients and come from the same predetermined area;
a parameter determining module 520, configured to obtain a first parameter and a second parameter of the client group in each historical popularization activity related to the activity to be promoted, where the first parameter is a difference between resource variation of a popularization group and resource variation of a comparison group in each historical popularization activity of the client group; the second parameter represents the proportion of the resource change configuration quantity of the customer group in the ranking position of the customer resource change quantity from small to large in each historical popularization activity;
the configuration module 530 is configured to determine a resource change configuration amount of the to-be-promoted activity according to a first parameter and a second parameter of the client group in each historical promotion activity related to the to-be-promoted activity.
In the embodiment, a client group of activities to be promoted is selected, and a first parameter and a second parameter of the client group in each historical promotion activity Xi related to the activities to be promoted are obtained; according to the first parameter and the second parameter of the client group in each historical popularization activity Xi related to the activity to be popularized, the resource change allocation amount of the activity to be popularized is determined, the feedback of the client group in the historical popularization activity (namely the relation between the first parameter and the second parameter of the client group in the historical popularization activity) can be fused into the allocation of the resource variation amount of the popularization activity under the condition that a multidimensional client group figure is lacked, the resource change allocation amount of the popularization activity can be accurately allocated, and therefore the popularization activity with high client participation degree and high standard reaching rate is designed.
In an embodiment of this document, as shown in fig. 6, the system for configuring a promotional activity further includes: a parameter calculation module 540, wherein the parameter calculation module 540 comprises: a first parameter calculating unit 541 and a second parameter calculating unit 542, wherein the first parameter calculating unit 541 is configured to calculate a first parameter after the promotion activity ends, and the second parameter calculating unit 542 is configured to calculate a second parameter after the promotion activity ends.
The process of the first parameter calculation unit 541 calculating the first parameter of each historical popularization activity includes: calculating the variation of the popularization group resources and the variation of the comparison group resources of the client group in the historical popularization activity; and subtracting the variation of the popularization group resource of the client group in the historical popularization activity from the variation of the comparison group resource, and calculating to obtain a first parameter of the client group in the historical popularization activity.
Wherein, calculating the resource variation of the promotion group and the resource variation of the comparison group in the historical promotion activities of the client group comprises: respectively calculating the total number of customers of the promotion group and the comparison group in the customer group; respectively calculating the variation of the total resources of the promotion group and the variation of the total resources of the comparison group in the historical promotion activities of the client group; calculating the promotion group resource variation of the client group in the historical promotion activity by dividing the promotion group total resource variation of the client group in the historical promotion activity by the promotion group client total number; and dividing the comparison group total resource variation of the client group in the historical popularization activity by the comparison group client total number to calculate the comparison group resource variation of the client group in the historical popularization activity.
The process of calculating the second parameter of each historical promotional activity by the second parameter calculation unit 542 includes: sequencing the resource variation of each client of the comparison group in the historical popularization activity of the client group from small to large; determining the ranking of the resource change configuration quantity of the historical popularization activity in the sequencing result; and dividing the ranking by the total number of the clients in the control group, and calculating to obtain a second parameter of the client group in the historical popularization activity.
In an embodiment of this document, the determining, by the configuration module 530, the resource change configuration amount of the activity to be promoted according to the first parameter and the second parameter of the client group in each historical promotion activity related to the activity to be promoted includes:
averaging the screened second parameters of the historical popularization activities of the N before ranking; taking the calculated average value as a second parameter configuration quantity of the activity to be promoted; screening out resource variation of clients in a comparison group of activities to be promoted from each historical promoting activity Xj in the latest M historical promoting activities, and sequencing the resource variation of the screened clients from small to large; and taking the average value or the maximum value of the resource variation quantity of which the sequencing position accounts for the second parameter configuration quantity in the latest M historical promotion activities as the resource variation configuration quantity of the activity to be promoted. In order to more clearly illustrate the technical solution herein, the following takes the bank developing the promotion activities as an example for detailed description, and as shown in fig. 7, the promotion activity configuration process includes:
(1) Retrieving the historical popularization activity with the highest first parameter from the first parameter and the second parameter of the historical popularization activity inquired in the step 730; taking a second parameter corresponding to the retrieved historical popularization activity as a second parameter configuration quantity of the activity to be popularized;
(2) Determining resource variation of the clients in the comparison group of the activities to be promoted from the latest relevant historical promotion activity of the activities to be promoted, and sequencing the resource variation from small to large;
(3) The position proportion in the sequence is the resource variation corresponding to the second parameter configuration quantity, and the resource variation is used as the resource variation configuration quantity T of the application activity to be developed at this time, and the activity to be promoted is developed;
the first parameter is: promotion group per capita asset variation-control group per capita asset variation.
The second parameter is as follows: and sequencing the asset variation of each person in the promotion activity period of the control group from small to large, determining the ranking of the resource variation configuration quantity T in the sequencing result, calculating the percentage of the ranking in the sequence, and taking the calculated percentage as a second parameter.
The method and the system can solve the problem that in an existing online banking customer operation scene, under the condition that a multidimensional customer group portrait is lacked, feedback of the customer group in historical popularization activities (namely the relation between a first parameter and a second parameter of the customer group in the historical popularization activities) is fused into the configuration of the resource variation of the popularization activities, the resource variation configuration quantity of the popularization activities can be accurately configured, and therefore the popularization activities with high customer participation degree, high responsiveness and high standard reaching rate are designed.
In an embodiment herein, there is also provided a computer device, as shown in fig. 8, the computer device 802 may include one or more processors 804, such as one or more Central Processing Units (CPUs), each of which may implement one or more hardware threads. The computer device 802 may also include any memory 806 for storing any kind of information, such as code, settings, data, etc. For example, and without limitation, memory 806 may include any one or more of the following in combination: any type of RAM, any type of ROM, flash memory devices, hard disks, optical disks, etc. More generally, any memory may use any technology to store information. Further, any memory may provide volatile or non-volatile retention of information. Further, any memory may represent fixed or removable components of computer device 802. In one case, when the processor 804 executes the associated instructions, which are stored in any memory or combination of memories, the computer device 802 can perform any of the operations of the associated instructions. The computer device 802 also includes one or more drive mechanisms 808, such as a hard disk drive mechanism, an optical disk drive mechanism, etc., for interacting with any memory.
In an embodiment of this document, a computer-readable storage medium is further provided, where the computer-readable storage medium stores a computer program, and the computer program is executed by a processor to perform the steps of the promotional activity configuring method according to any one of the above embodiments.
Embodiments herein also provide a computer readable instruction, wherein when the instruction is executed by a processor, the program causes the processor to execute the steps of the promotional activity configuration method according to any of the above embodiments.
It should be understood that, in various embodiments herein, the sequence numbers of the above-mentioned processes do not mean the execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments herein.
It should also be understood that, in the embodiments herein, the term "and/or" is only one kind of association relation describing an associated object, meaning that three kinds of relations may exist. For example, a and/or B, may represent: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship.
Those of ordinary skill in the art will appreciate that the various illustrative components and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the components and steps of the various examples have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present disclosure.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided herein, it should be understood that the disclosed system, apparatus, and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one type of logical functional division, and other divisions may be realized in practice, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may also be an electrical, mechanical or other form of connection.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one position, or may be distributed on multiple network units. Some or all of the units can be selected according to actual needs to achieve the purposes of the embodiments herein.
In addition, functional units in the embodiments herein may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present invention may be implemented in a form of a software product, which is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the methods described in the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The principles and embodiments of this document are explained herein using specific examples, which are presented only to aid in understanding the methods and their core concepts; meanwhile, for a person skilled in the art, according to the idea of the present disclosure, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present disclosure should not be construed as a limitation to the present disclosure.
Claims (10)
1. A method for configuring a promotional campaign, comprising:
selecting a client group to be promoted, wherein the client group comprises a promotion group and a comparison group;
acquiring a first parameter and a second parameter of the client group in each historical popularization activity related to the activity to be popularized, wherein the first parameter represents a difference value of resource variation of a popularization group and a comparison group of the client group in one historical popularization activity; the second parameter represents the proportion of the resource change configuration quantity of the client group in the ranking position of the client resource change quantity from small to large in the comparison group in the historical popularization activity;
and determining the resource change allocation amount of the activities to be promoted according to the first parameter and the second parameter of the client group in each historical promotion activity related to the activities to be promoted.
2. The method of claim 1, wherein the promotion group and the control group have the same number of customers and the customers have the same characteristic distribution and come from the same predetermined area.
3. The method of claim 1, wherein the calculating of the first parameter of the customer base during each historical promotional activity comprises:
for each historical promotional activity Xi, the following operations are performed:
calculating the variation of the popularization group resources and the variation of the comparison group resources of the client group in the historical popularization activity Xi;
and subtracting the variation of the popularization group resource of the client group in the historical popularization activity Xi from the variation of the reference group resource, and calculating to obtain a first parameter of the client group in the historical popularization activity Xi.
4. The method of claim 3, wherein calculating the variation of the promoted group resource and the variation of the control group resource of the client group in the historical promoted activities comprises:
respectively calculating the total number of customers of the promotion group and the comparison group in the customer group;
respectively calculating the variation of total resources of the promotion group and the variation of total resources of the comparison group of the client group in the historical promotion activities;
calculating the promotion group per-capita resource variation of the client group in the historical promotion activity by dividing the promotion group total resource variation of the client group in the historical promotion activity by the promotion group total client number;
and dividing the comparison group total resource variation of the client group in the historical popularization activity by the comparison group client total number to calculate the comparison group per-capita resource variation of the client group in the historical popularization activity.
5. The method of claim 1, wherein determining the resource change allocation amount of the to-be-promoted activity according to a first parameter and a second parameter of the customer base in each historical promotion activity related to the to-be-promoted activity comprises:
screening out the historical popularization activities with the first parameter ranked N before according to the first parameter of the client group in each historical popularization activity related to the activity to be popularized;
and calculating the resource change allocation amount of the activity to be promoted according to the screened second parameter of the historical promotion activity of the N before the ranking.
6. The method of claim 5, wherein calculating the resource change configuration amount of the activity to be promoted according to the screened second parameter of the historical promotion activity of the N-top ranking comprises:
carrying out maximum value solving or average processing on the screened second parameter of the historical popularization activity of the N before ranking;
taking the calculated value as a second parameter configuration quantity of the activity to be promoted;
and calculating the resource change allocation quantity of the activity to be promoted according to the second parameter allocation quantity and the latest M historical promotion activities related to the activity to be promoted.
7. The method of claim 6, wherein calculating the resource change configuration quantity of the activity to be promoted according to the second parameter configuration quantity and the recent M historical promotion activities related to the activity to be promoted comprises:
screening out resource variation of clients in a comparison group of the activities to be promoted from each historical promoting activity Xj in the latest M historical promoting activities, and sequencing the resource variation of the screened clients from small to large;
and taking the average value or the maximum value of the resource variation quantity of which the sequencing position accounts for a second parameter configuration quantity in the latest M historical popularization activities as the resource variation configuration quantity of the activities to be popularized.
8. A promotional activity configuration system, comprising:
the client group selection module is used for selecting a client group to be promoted, and the client group comprises a promotion group and a comparison group;
the parameter determining module is used for acquiring a first parameter and a second parameter of the client group in each historical promotion activity related to the activity to be promoted, wherein the first parameter represents a difference value of resource variation of a promotion group and a comparison group of the client group in one historical promotion activity; the second parameter represents the proportion of resource change configuration quantity of the client group in the ordering position from small to large of the client resource change quantity in the comparison group in a historical popularization activity;
and the configuration module is used for determining the resource change configuration amount of the activities to be promoted according to the first parameter and the second parameter of the client group in each historical promotion activity related to the activities to be promoted.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the promotional activity configuration method of any of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium stores an executable computer program, which when executed by a processor implements the promotional activity configuration method of any of claims 1 to 7.
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